{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.mlab as mlab\n",
    "import math\n",
    "import pandas as pd\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = [10,100,200,300,400, 600,700,800,1000]\n",
    "y = [600,350,300,200,100, 100,150,200,400]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "z1 = np.polyfit(x, y, 3)\n",
    "xx = [a for a in range(x[-1])]\n",
    "yvals = np.polyval(z1,xx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RpVO9N+3220d3zvDhsdNVqXvllejuevDBWL4AYqjk6NGwzz5qwWedgl4yY9Om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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1190973c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xx, yvals, color = '#3333ff',linewidth=2)\n",
    "ax=plt.gca()\n",
    "# ax.set_xlim([x[0]-20, x[-1]+20])\n",
    "ax.set_ylim([50, 620])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
